The University of Southampton
University of Southampton Institutional Repository

Validating the portal population of the United Kingdom Multiple Sclerosis Register

Validating the portal population of the United Kingdom Multiple Sclerosis Register
Validating the portal population of the United Kingdom Multiple Sclerosis Register

The UK Multiple Sclerosis Register (UKMSR) is a large cohort study designed to capture ‘real world’ information about living with multiple sclerosis (MS) in the UK from diverse sources. The primary source of data is directly from people with Multiple Sclerosis (pwMS) captured by longitudinal questionnaires via an internet portal. This population's diagnosis of MS is self-reported and therefore unverified. The second data source is clinical data which is captured from MS Specialist Treatment centres across the UK. This includes a clinically confirmed diagnosis of MS (by Macdonald criteria) for consented patients. A proportion of the internet population have also been consented at their hospital making comparisons possible. This dataset is called the ‘linked dataset’. The purpose of this paper is to examine the characteristics of the three datasets: the self-reported portal data, clinical data and linked data, in order to assess the validity of the self-reported portal data. The internet (n = 11,021) and clinical (n = 3,003) populations were studied for key shared characteristics. We found them to be closely matched for mean age at diagnosis (clinical = 37.39, portal = 39.28) and gender ratio (female %, portal = 73.1, clinical = 75.2). The Two Sample Kolmogorov-Smirnov test was for the continuous variables to examine is they were drawn from the same distribution. The null hypothesis was rejected only for age at diagnosis (D = 0.078, p < 0.01). The populations therefore, were drawn from different distributions, as there are more patients with relapsing disease in the clinical cohort. In all other analyses performed, the populations were shown to be drawn from the same distribution. Our analysis has shown that the UKMSR portal population is highly analogous to the entirely clinical (validated) population. This supports the validity of the self-reported diagnosis and therefore that the portal population can be utilised as a viable and valid cohort of people with Multiple Sclerosis for study.

Data linkage, Longitudinal, Multiple sclerosis, PROMs, Research register, Validation
2211-0348
3-10
Middleton, R.M.
793f911e-f5a8-48af-8c64-632036105722
Rodgers, W.J.
d7881fb6-145d-4ff2-921b-c121570ae2ce
Chataway, J.
7724d157-1f90-4cca-ba06-db0a4719e199
Schmierer, K.
dcc9ae69-7ec3-469f-94b2-ec34033ba345
Rog, D.
453e5c28-6871-4c10-953b-be1dcd07059f
Galea, I.
66209a2f-f7e6-4d63-afe4-e9299f156f0b
Akbari, A.
7a8ecb03-08e5-47e0-bf8d-b1ec9f314b53
Tuite-Dalton, K.
addc00c1-d6dd-4188-8828-96b5d2208dd5
Lockhart-Jones, H.
2f05db18-acbb-46ed-b534-6c80c4c81591
Griffiths, D.
c77efef0-07f2-4fe4-b5c5-36a00d843333
Noble, D.G.
7f0cee1f-2c76-423d-ad6d-17d77ec719c1
Jones, K.H.
840f4757-077b-4947-8e2d-38c363fa066a
Al-Din, A.
55fa7d7c-66c4-4c36-a363-5768c147f613
Craner, M.
15bde954-b5bb-40f5-a66f-120887b8ec09
Evangelou, N.
21e17730-dd94-4d25-a2b4-b563913c959f
Harman, P.
fedb471b-6ab3-4d38-9eaf-b5b6611f179f
Harrower, T.
622aef99-ac5d-4ec5-8c02-03a78cbaebcb
Hobart, J.
61bd2058-a882-4cc0-9f08-c4411de853d7
Husseyin, H.
55300b41-2a59-417e-b099-927a4bbbf146
Kasti, M.
4f592861-07ca-45f8-9462-c6670f81241e
Kipps, C.
e43be016-2dc2-45e6-9a02-ab2a0e0208d5
McDonnell, G.
43c8d4e6-b68c-4694-9bbd-93d87764c1e5
Owen, C.
4e3528d2-6813-41bf-a244-1a1085fada63
Pearson, O.
fb48c15b-5349-4117-be35-2fd178367fca
Rashid, W.
81076cf3-2fdc-4d55-8a0e-80604ef618ff
Wilson, H.
9a48b1f2-494b-42cf-a02c-c0a0e9967d33
Ford, D.V.
07bf2ec1-e5dd-4f45-9ba0-1726fde70d1b
Middleton, R.M.
793f911e-f5a8-48af-8c64-632036105722
Rodgers, W.J.
d7881fb6-145d-4ff2-921b-c121570ae2ce
Chataway, J.
7724d157-1f90-4cca-ba06-db0a4719e199
Schmierer, K.
dcc9ae69-7ec3-469f-94b2-ec34033ba345
Rog, D.
453e5c28-6871-4c10-953b-be1dcd07059f
Galea, I.
66209a2f-f7e6-4d63-afe4-e9299f156f0b
Akbari, A.
7a8ecb03-08e5-47e0-bf8d-b1ec9f314b53
Tuite-Dalton, K.
addc00c1-d6dd-4188-8828-96b5d2208dd5
Lockhart-Jones, H.
2f05db18-acbb-46ed-b534-6c80c4c81591
Griffiths, D.
c77efef0-07f2-4fe4-b5c5-36a00d843333
Noble, D.G.
7f0cee1f-2c76-423d-ad6d-17d77ec719c1
Jones, K.H.
840f4757-077b-4947-8e2d-38c363fa066a
Al-Din, A.
55fa7d7c-66c4-4c36-a363-5768c147f613
Craner, M.
15bde954-b5bb-40f5-a66f-120887b8ec09
Evangelou, N.
21e17730-dd94-4d25-a2b4-b563913c959f
Harman, P.
fedb471b-6ab3-4d38-9eaf-b5b6611f179f
Harrower, T.
622aef99-ac5d-4ec5-8c02-03a78cbaebcb
Hobart, J.
61bd2058-a882-4cc0-9f08-c4411de853d7
Husseyin, H.
55300b41-2a59-417e-b099-927a4bbbf146
Kasti, M.
4f592861-07ca-45f8-9462-c6670f81241e
Kipps, C.
e43be016-2dc2-45e6-9a02-ab2a0e0208d5
McDonnell, G.
43c8d4e6-b68c-4694-9bbd-93d87764c1e5
Owen, C.
4e3528d2-6813-41bf-a244-1a1085fada63
Pearson, O.
fb48c15b-5349-4117-be35-2fd178367fca
Rashid, W.
81076cf3-2fdc-4d55-8a0e-80604ef618ff
Wilson, H.
9a48b1f2-494b-42cf-a02c-c0a0e9967d33
Ford, D.V.
07bf2ec1-e5dd-4f45-9ba0-1726fde70d1b

Middleton, R.M., Rodgers, W.J., Chataway, J., Schmierer, K., Rog, D., Galea, I., Akbari, A., Tuite-Dalton, K., Lockhart-Jones, H., Griffiths, D., Noble, D.G., Jones, K.H., Al-Din, A., Craner, M., Evangelou, N., Harman, P., Harrower, T., Hobart, J., Husseyin, H., Kasti, M., Kipps, C., McDonnell, G., Owen, C., Pearson, O., Rashid, W., Wilson, H. and Ford, D.V. (2018) Validating the portal population of the United Kingdom Multiple Sclerosis Register. Multiple Sclerosis and Related Disorders, 24, 3-10. (doi:10.1016/j.msard.2018.05.015).

Record type: Article

Abstract

The UK Multiple Sclerosis Register (UKMSR) is a large cohort study designed to capture ‘real world’ information about living with multiple sclerosis (MS) in the UK from diverse sources. The primary source of data is directly from people with Multiple Sclerosis (pwMS) captured by longitudinal questionnaires via an internet portal. This population's diagnosis of MS is self-reported and therefore unverified. The second data source is clinical data which is captured from MS Specialist Treatment centres across the UK. This includes a clinically confirmed diagnosis of MS (by Macdonald criteria) for consented patients. A proportion of the internet population have also been consented at their hospital making comparisons possible. This dataset is called the ‘linked dataset’. The purpose of this paper is to examine the characteristics of the three datasets: the self-reported portal data, clinical data and linked data, in order to assess the validity of the self-reported portal data. The internet (n = 11,021) and clinical (n = 3,003) populations were studied for key shared characteristics. We found them to be closely matched for mean age at diagnosis (clinical = 37.39, portal = 39.28) and gender ratio (female %, portal = 73.1, clinical = 75.2). The Two Sample Kolmogorov-Smirnov test was for the continuous variables to examine is they were drawn from the same distribution. The null hypothesis was rejected only for age at diagnosis (D = 0.078, p < 0.01). The populations therefore, were drawn from different distributions, as there are more patients with relapsing disease in the clinical cohort. In all other analyses performed, the populations were shown to be drawn from the same distribution. Our analysis has shown that the UKMSR portal population is highly analogous to the entirely clinical (validated) population. This supports the validity of the self-reported diagnosis and therefore that the portal population can be utilised as a viable and valid cohort of people with Multiple Sclerosis for study.

Text
Validating the Portal Population of the MS Register_preprint - Accepted Manuscript
Download (978kB)

More information

Accepted/In Press date: 22 May 2018
e-pub ahead of print date: 25 May 2018
Published date: 1 August 2018
Keywords: Data linkage, Longitudinal, Multiple sclerosis, PROMs, Research register, Validation

Identifiers

Local EPrints ID: 422712
URI: http://eprints.soton.ac.uk/id/eprint/422712
ISSN: 2211-0348
PURE UUID: 6c1c2e66-de1f-4582-ab68-661a67a6144c
ORCID for I. Galea: ORCID iD orcid.org/0000-0002-1268-5102
ORCID for C. Kipps: ORCID iD orcid.org/0000-0002-5205-9712

Catalogue record

Date deposited: 31 Jul 2018 16:30
Last modified: 22 Apr 2024 01:52

Export record

Altmetrics

Contributors

Author: R.M. Middleton
Author: W.J. Rodgers
Author: J. Chataway
Author: K. Schmierer
Author: D. Rog
Author: I. Galea ORCID iD
Author: A. Akbari
Author: K. Tuite-Dalton
Author: H. Lockhart-Jones
Author: D. Griffiths
Author: D.G. Noble
Author: K.H. Jones
Author: A. Al-Din
Author: M. Craner
Author: N. Evangelou
Author: P. Harman
Author: T. Harrower
Author: J. Hobart
Author: H. Husseyin
Author: M. Kasti
Author: C. Kipps ORCID iD
Author: G. McDonnell
Author: C. Owen
Author: O. Pearson
Author: W. Rashid
Author: H. Wilson
Author: D.V. Ford

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×